proteomik dengan high- resolution mass spectrometry (hrms...

Proteomik dengan High-Resolution Mass Spectrometry

(HRMS) untuk Analisis HalalTri Joko Raharjo

Keberadaan komponen non halal pada makanan danbahan obat?

• Motivasi ekonomi: RpRpRp• Penggantian atau penambahan daging dengan daging lain dalam rangka

menurunkan biaya produksi dan mendapatkan untuk lebih banyak

• Harga daging babi << daging sapi

• Ketidakcukupan suplai bahan yang halal• Gelatin yang dari material halal ???

• Apa konsekwensinya?• Terjadi pelanggaran hukun (pemalsuan)

• Keselamatan dan keamanan konsumen (alergi dll)

• Masalah etika, budaya dan agama

Metode analisis halal

• Two-dimensional polyacrylamide gel electrophoresis and western-blot analysis

• PCR dan Real-Time PCR

• Enzyme-linked immunosorbent assay (ELISA)

Beberapa kekurangan• Sebagian besar kualitatif

• Tidak selalau bisa digunakan (PCR untuk gelatin?)

• Data tidak dapat dapat diekplorasi lagi untuk data mining

Bottom-up proteomics sebagai dasar pengembangananalisis berbasis MS

• Semua makhluk hidup mempunyai hubungankekerabatan secara genetic

• Filogeni menunjukkan diversitas dan hubungankekerabatan.

• Filogeni dibuat dengan menggunakan urutanDNA.

• Hubungan antara gen dengan spesies(variabilitas) menjadi sentral dalam analisis halal

Evolusi molekuler dari DNA ke protein

-GGAGCCATATTAGATAGA-

-GGAGCAATTTTTGATAGA-

Gly Ala Ile Leu asp Arg

Gly Ala Ile Phe asp Arg

• 3 perbedaan nukeotida DNA padatiga kodon hanya menyebabkanperbedaan satu asam amino

• 2 penggantian nucleotidadikatakan sinonim dan satupenggantian lain disebut non-sinonim

Terdapat lebih satu kodon untuksetiap asam amino.

Menemukan urutan protein spesifikspesies menjadi semakin kompleksdisbanding urutan DNA, tetapi lebih

menjanjikan untuk pembeda

Bagaimana bottom-up proteomics digunakan untukidentifikasi asal species suatu bahan?

Phase 1Proteome mapping

Targetedproducts

Protein Extraction

Proteolysis

Peptide enrichment

MS and MS/MS

Protein / peptide identification

Genome annotation

Bottom

Up !

Trypsin

In silico

Precursor massesPeptide mass fingerprinting

Eksperimen

Define Set of Proteins

Select Peptides

Select precursor and product ions

Validate precursor and product ions

Protein Detection and Quantitation

5’ 3’

3’ 5’DNA

mRNA

Protein

Proteotypic peptides

MS/MS spectra

Fractionation

Digestion

LC-MS

Homogenization/

MS

Shotgun proteomics Targeted MS

1. Records m/z

2. Selects peptides based on abundance and fragments

MS/MS

3. Protein database search for peptide identification

Data Dependent Acquisition (DDA)Data Independent Acquisition (IDA)

Uses predefined set of peptides for routine typing analyses

1. Select precursor ion

MS

2. Specific Precursor fragmentation

MS/MS

3. Use Precursor-Fragment pairs for identification

Genome

Transcriptome

Proteome

Common protein

sequences

Species 1 Species 2

Species 3 Species 4

Generate proteotypicspecies specific mass lists

Precursor ions

Generate MS/MS product ion species specific mass

lists

Survey MS Scan

Precursor ions

Acquired MS/MS

Product ions

Database survey

MASCOT /

SEQUEST

Genome

(speciation)

Peptide

Fingerprinting

PMF

In Silico

In Silico

MS and MS

Analysis

Peptide biomarkers

based speciation

Experimental

Experimental

Preparasi sampel pada Bottom-up proteomics1. Sampel (daging) dicampur air (1:5) is homogenisasi, sonikasi

2. Protein dalam suspensi diendapkan dengan aseton (1:1)

3. Aseton dipisahkan menghasilkan pellet protein

4. Pelet protein dilarutkan dalam ammonium bicarbonate (pH 8.5).

5. Denaturasi protein pada 120˚C

6. Reduksi protein dengan Dithiothreitol (DTT) dan alkilasi dengan Iodoacetamide IAA

7. Gidesti dengan trypsin pada 40 C selama 24jam. Trypsin memotong ujung C: Lys (K) & Arg (R)

+

H2O

I. II. III. IV.

Survey MS Scan

Select ions of interest

(mass range)

Acquired MS/MS spectra

LC-MSQqQ

LIT or QITHybrid Q-Orbitrap

Thermo Scientific™ UltiMate ™ 3000 LC system and Thermo Scientific™ TSQ Quantiva MS

UltiMate 3000 LC system and Thermo Scientific™ Q Exactive™ Hybrid Quadrupole-Orbitrap MS

Otentifikasi daging dengan mass spectrometry

• Bargen et al. (2013), Journal of Agricultural and Food Chemistry, 61:11986-11994

Peptide biomarkers

?

Pendekatan Peptide Fingerprinting

0 5 10 15 20 25 30 35 40 45

Time (min)

Porcine TICSus scrofa

Generate a mass list (MS and MS/MS data)

Database search (MASCOT)

MS and MS/MS matching

Peptide fingerprinting

7 429 common unique peptides

identified

Beef Horse

LambPork

17 specific peptides

9 specific peptides14 specific peptides

23 specific peptides

Using a relatively high abundance threshold …

Several peaks used were not adequately identified

PMF

Bargen et al. (2013), Journal of Agricultural and Food Chemistry, 61:11986-11994

Kelemahan PMF• Tergantung pada data MS dan MS/MS• Tergantung setting parameter dalam bioinformatik• Memerlukan ekspert proteomic dan bioinformatik

Sulit diaplikasikan untuk analisis rutin

Apakah ada alternatif lain?

Genome

Transcriptome

Proteome

Common protein

sequences

Beef Horse

Pork Lamb

mRNA

Protein

TrypticPeptides

Species specific peptide mass databasePrecursor ions

Species specific product ions database

Survey MS Scan

Select ions

of interest


Generation of post-analysis XICs for

selected proteotyping peptides

Peptide biomarkers

based speciation

Targeted bioinformatics analysisDaging: Myoglobin

Extraction of gene information

In silico sequence alignment

In silico protein translation and alignment

Sequence analysis and In silico tryptic digestion

Generate proteotypicmass lists

Proteotypic peptides can be identified(120-134)

YLEFISDA IIHVLHAKHP SDFGADAQAA MSKALELFRYLEFISDA IIHVLHSKHP GDFGADAQGA MTKALELFRYLEFISEA IIQVLQSKHP GDFGADAQGA MSKALELFRYLEFISDA IIHVLHAKHP SDFGADAQGA MSKALELFR

120 134

BeefHorsePorkLamb

Myoglobin adalah protein pembawa oksigen di jaringan ototKeberadaannya melimpah di otot/daging vertebrata termasuk mamalia

18VEADVAGHGQEVLIRLFK35

36GHPETLEK43

52SEDEMKASEDLK63

81GHHEAELTPLAQSHATK97

104YLEFISEAIIQVLQSK119

Specific pork myoglobin tryptic peptides

Specific MS and MS/MS data

Contoh protein lain

Myosin-1 (MYH1)

Myosin-2 (MYH2)

β Hemoglobin (Hbb)

Myoglobin (MB)

MB 120-134

Species Tryptic Peptide sequence (biomarker) Theoritical mass (z=2)

Pork HPGDFGADAQGAMSK 744.8304

Horse HPGDFGADAQGAMTK 751.8383

Beef HPSDFGADAQAAMSK 766.8435

Lamb HPSDFGADAQGAMSK 759.8357

Chicken HAADFGADSQAAMKKHAADFGADSQAAMK

774.3672710.3197

Myosin-1 (MYH1)

MYH1 619-638


Pork TLAFLFTGAAGADAEAGGGK 912.9600

Horse TLALLFSGPASADAEAGGK 888.4623

Beef TLALLFSGPASGEAEGGPK 901.4702

Lamb TLAFLFSGAASAEAEGGGAK 927.9652

Chicken TLALLFASAGGEPEASGGGGK 945.4838

Myosin-2 (MYH2)

MYH2 619-638


Pork TLAFLFSGAQTGEAEAGGTK 978.4891

Horse TLALLFSGAQTADAEAGGVK 960.5073

Beef TLAFLFSGTPTGDSEASGGTK 1022.4971

Lamb TLALLFSGTPTAESEGSGTK 984.0020

Chicken TLALLFANYGGAEAEASGGGGGGK 1084.5346

β-Hemoglobin

βHG 42-60


Pork FFESFGDLSNADAVMGNPK 1023.4673

Horse FFDSFGDLSNPGAVMGNPK 1000.4646

Beef FFESFGDLSTADAVMNNPK 1045.4804

Lamb FFEHFGDLSNADAVMNNPK 1076.9915

Chicken FFASFGNLSSPTAILGNPMVR 1113.5724

Myoglobin Myosin-1 Myosin-2 β-HaemoglobinPork 120HPGDFGADAQGAMSK140 619TLAFLFTGAAGADAEAGGGK638 619TLAFLFSGAQTGEAEAGGTK638 42FFESFGDLSNADAVMGNPK60

Horse 120HPGDFGADAQGAMTK140 619TLALLFSGPASADAEAGGK637 617TLALLFSGAQTADAEAGGVK636 42FFDSFGDLSNPGAVMGNPK60

Beef 120HPSDFGADAQAAMSK140 619TLALLFSGPASGEAEGGPK637 619TLAFLFSGTPTGDSEASGGTK639 40FFESFGDLSTADAVMNNPK58

Lamb 120HPSDFGADAQGAMSK140 619TLAFLFSGAASAEAEGGGAK638 617TLALLFSGTPTAESEGSGTK636 40FFEHFGDLSNADAVMNNPK58

Chicken 120HAADFGADSQAAMKK140 618TLALLFASAGGEPEASGGGGK638 618TLALLFANYGGAEAEASGGGGGGK642 42FFASFGNLSSPTAILGNPMVR62

In silico MS2

fragmentation prediction

Venn diagrams

Otentifikasi dapat dilakukan pada MS1 dan MS2 untuk meningkatkan spesifisitas

Analisis Bioinformatik

Peptida target dicobakan untuk MS2 dimanadihasilkan fragmen unik b dan y.

P E T L E K

P E T L E

P E T L

P E T

P E

E T L E K

T L E K

L E K

E K

b fragment ions y fragment ions

Analisis myoglobin dengan digesti proteolitik

Strategy

Survey MS Scan

Select ions

of interest

Acquired MS/MS

spectra



Beef Horse Pork Lamb

766.8435 (z=2)

751.8383(z=2)

744.8304(z=2)

759.8357(z=2)

140 000 FWHMm/z 500-2000

17 500 FWHM

Isolation width = 1.5 AMU

Extracted ion chromatograms with mn ± 5 ppm

Setiap target peptide diekstrak dari TIC

749.0 749.5 750.0 750.5 751.0 751.5 752.0 752.5 753.0 753.5 754.0 754.5 755.0

m/z

751.8378

752.3393

752.8404

753.3409

∆m is - 0.7 ppmTIC masih mengandunglebih dari 7000 peptida

Identifikasi spesifikproduk ion

Survey MS Scan

Select ions

of interest

Acquired MS/MS

spectra



Beef Horse Pork Lamb

766.8435 (z=2)

751.8383(z=2)

744.8304(z=2)

759.8357(z=2)

140 000 FWHMm/z 500-2000

17 500 FWHM

Isolation width = 1.5 AMU Beef Horse Pork Lamb

1298.5681 (y13)

1268.5576 (y13)

1254.5419 (y13)

1284.5525 (y13)

1395.6209 (y14)

1365.6103 (y14)

1351.5947 (y14)

1381.6053 (y14)

XIC untuk y14 atau y13 ± 5 ppm

766.8 1298.5681 (y13) 766.8 1395.6209 (y14)

751.8 1268.5576 (y13)

744.8 1254.5419 (y13)

759.8 1284.5525 (y13)

751.8 1365.6103 (y14)

744.8 1351.5947 (y14)

759.8 1381.6053 (y14)

XIC spesifik dapatdigunakan untukmembedaan antarspesies , tetapi….

Beef

Horse

Pork

Lamb

Overlay XIC (extracted ion chromatogram) m/z 744.8304 ± 5 ppm (z=2)Peptida myoglobin babi

0 5 10 15 20 25 30 35 40 45

Time (min)

100%

50%

25%

10%

1%

Peak area XIC vs konsentrasi

0 20 40 60 80 1000

1000000

2000000

3000000

% W/W

Pe

ak A

rea

R2 = 0.9676

Sam

ple

1

Sam

ple

2

Sam

ple

3

Sam

ple

40.0

5.0×106

1.0×107

1.5×107

2.0×107

2.5×107

Pe

ak A

rea

Presisi

Sam

ple

1

Sam

ple

2

Sam

ple

3

Sam

ple

40.0

5.0×107

1.0×108

1.5×108

2.0×108

2.5×108

3.0×108

3.5×108

Pe

ak A

rea

Beef (Myoglobin peptide 120-134)

% CV < 20%

Sam

ple

1

Sam

ple

2

Sam

ple

3

Sam

ple

40.0

5.0×107

1.0×108

1.5×108

2.0×108

Pe

ak A

rea

Horse (Myoglobin peptide 120-134)

% CV < 16%

Pork (Myoglobin peptide 120-134)

% CV < 22%

Sam

ple

1

Sam

ple

2

Sam

ple

3

Sam

ple

40

1×107

2×107

3×107

4×107

Pe

ak A

rea

Lamb (Myoglobin peptide 120-134)

% CV < 19%

0 5 10 15 20 25 30 35 40 45

Time (min)

Rel

ativ

e ab

unda

nce

(%)

7 8 9 10

Time (min)

Rel

ativ

e ab

unda

nce

(%)

16 17 18 19Time (min)

Rel

ativ

e ab

und

ance

(%

)

15 16 17 18Time (min)

Rel

ativ

e ab

und

ance

(%

)

15 16 17 18Time (min)

Rel

ativ

e a

bund

ance

(%

)

0 5 10 15 20 25 30 35 40 45

Time (min)

Rel

ativ

e ab

und

ance

(%

)

7 8 9 10

Time (min)

Rel

ativ

e ab

und

ance

(%

)

16 17 18 19

Time (min)

Rel

ativ

e a

bu

ndan

ce (

%)

15 16 17 18Time (min)

Rel

ativ

e ab

und

anc

e (%

)

15 16 17 18Time (min)

Re

lativ

e a

bun

danc

e (

%)

0 5 10 15 20 25 30 35 40 45

Time (min)

Re

lativ

e a

bund

ance

(%

)

7 8 9 10

Time (min)

Rel

ativ

e a

bund

ance

(%

)

16 17 18 19

Time (min)

Rel

ativ

e ab

unda

nce

(%

)

15 16 17 18Time (min)

Rel

ativ

e ab

und

anc

e (

%)

15 16 17 18Time (min)

Re

lativ

e ab

und

ance

(%

)

A B C

Myoglobin (120-134)HPGDFGADAQGAMSKXIC 744.8304 (± 5 ppm)

Myosin-1 (619-638)TLAFLFTGAAGADAEAGGGKXIC 912.9600 (± 5 ppm)

Myosin-2 (619-638)TLAFLFSGAQTGEAEAGGTKXIC 978.4891 (± 5 ppm)

β-HaemoglobinFFESFGDLSNADAVMGNPKXIC 1023.4673 (± 5 ppm)

sapi kambing ayam

Sampel daging dispike dengan 1% (w/w) babi

Warna merah untuk daging tanpa spiking

Data-independent acquisition (DIA)

Full scan m/z 600 – 1200 70, 000 FWHM

m/z 600-650

MS/MS isolation range

m/z 650-700

m/z 700-750

m/z 750-800

m/z 800-850

m/z 850-900

m/z 900-950

m/z 950-1000

m/z 1000-1050

m/z 1050-1100

m/z 1100-1150

m/z 1150-1200

17 500 FWHMAGT: 1e6

Isolation with : 50 DAMSX count: 1Loop count: 6Max IT: Auto

Precursor mass m/z 744.8304 (+2)

HPGDFGADAQGAMSK

1254.5419 (y13)

1351.5947 (y14)

Example: Pork myoglobin proteotypic peptide (120-134)

Specific fragment ions

0 25 50 75 1000.0

5.0×105

1.0×106

1.5×106

2.0×106

2.5×106

Concentration (% w/w)

Pe

ak A

rea

R2 > 0.98

0 25 50 75 1000

2×104

4×104

6×104

8×104

Concentration (% w/w)

Pe

ak A

rea

y14

y13

R2 > 0.95

MS1 data MSX dataDIA data

STRATEGI UMUMExtraction of gene

information

In silico sequence alignment

In silico protein translation and

alignment

Sequence analysis and In silico tryptic

digestion

Generate proteotypicmass lists

Survey MS Scan

Targeted MS/MS or

DIA (25 or 50 Da)




Precursor and specific production ions

Generate MS/MS product ion mass lists

Select ions

of interest

Speciation is therefore based on genetic

differences

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